Deviated well anisotropic formation three-dimensional induction logging data inversion method and apparatus

Abstract

A deviated well anisotropic formation three-dimensional induction logging data inversion method, comprising: carrying out azimuth angle conversion on pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve under a wellbore coordinate system (100); constructing a window function on the basis of morphological characteristics of the three-dimensional induction logging curve (200); segmenting the three-dimensional induction logging curve by means of the window function (300); and performing full-parameter inversion on each section of the three-dimensional induction logging curve to obtain a horizontal resistivity and vertical resistivity of each formation layer, formation boundaries and a well deviation angle, wherein an objective function of the full-parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve (400). The present application further relates to a deviated well anisotropic formation three-dimensional induction logging data inversion apparatus.

Description

Three-dimensional induction logging data inversion method and device for anisotropic formation in inclined well

[0001] Related Applications

[0002] This application claims priority to Chinese Patent Application No. 202410622248.5, filed on May 20, 2024, and incorporates by reference the entire disclosure of the aforementioned patent application as part of this application. TECHNICAL FIELD

[0003] The present application belongs to the technical field of oil and gas field exploration and development, in particular to the technical field of logging data processing, and specifically relates to a three-dimensional induction logging data inversion method and device for anisotropic formation in inclined well. BACKGROUND

[0004] It is estimated that about 30% of the oil and gas reserves in the world are stored in sand-shale thin interbeds. This kind of thin interbedded reservoir can be equivalent to a macroscopic uniaxial anisotropic formation (or, referred to as a transverse isotropic formation, abbreviated as TI formation), so detecting and identifying this kind of formation is of great significance to the development of oil and gas resources.

[0005] For existing axial induction logging instruments, the longitudinal resolution is not high enough, so in actual production, this kind of thin interbedded oil reservoir is often mistaken for a high water saturation layer and is missed.

[0006] A three-dimensional induction logging instrument is composed of three mutually perpendicular transmitting coils and three receiving coils parallel thereto, which can detect the horizontal and vertical conductivity information of the formation and identify the formation characteristics from a three-dimensional perspective, and has an inherent advantage in the detection of thin reservoirs and complex reservoirs. However, in general, the logging response of a three-dimensional induction instrument in an inclined well is related to the horizontal and vertical conductivities of the formation and the hole angle, and is highly nonlinear. In addition, the influence of adjacent layers on different components of the logging response is different, which increases the difficulty of logging data processing and interpretation and evaluation.

[0007] In the prior art, the three-dimensional induction logging data processing is mainly a multi-parameter nonlinear iterative inversion method. Iterative inversion needs to obtain formation parameters by fitting logging data through multiple forward calculations. If several hundred or even thousands of kilometers of logging data including hundreds of layers of formation are inverted together, it is very difficult, and the main reasons are as follows.

[0008] The calculation is large and the calculation speed is slow. The main reason is that the three-dimensional induction logging response has many components and complex relationships. At the same time, it is affected by various environmental factors such as formation, dip angle and adjacent layers. In addition, the derivative matrix (Jacobian matrix) of the formation parameters needs to be calculated and solved in iterative inversion.

[0009] The multi-value is serious and the stability is poor. Mainly because the inversion processing of the three-dimensional induction logging data belongs to a local optimization problem in mathematics, the multi-value and instability are its inherent properties. The several hundred formation parameters to be solved are easy to have equivalent relationship with each other, which leads to that the inversion program cannot find the real solution in the solving process, and the inversion program is unstable and does not converge. SUMMARY

[0010] An object of the present application is to provide a three-dimensional induction logging data inversion method for anisotropic formation in a deviated well, so that the method can quickly and accurately obtain parameters such as conductivity and hole angle of the anisotropic (TI) formation in the deviated well, and the three-dimensional induction logging data can be better processed and applied on site.

[0011] Another object of the present application is to provide a three-dimensional induction logging data inversion device for anisotropic formation in a deviated well. Still another object of the present application is to provide an electronic device including a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the three-dimensional induction logging data inversion method for anisotropic formation in a deviated well when executing the computer program. Another object of the present application is to provide a readable medium having a computer program stored thereon, and the computer program implements the steps of the three-dimensional induction logging data inversion method for anisotropic formation in a deviated well when executed by a processor.

[0012] To solve the technical problems in the background art, the present application provides the following technical solutions:

[0013] In a first aspect, the present application provides a three-dimensional induction logging data inversion method for anisotropic formation in a deviated well, comprising:

[0014] Conducting azimuthal conversion on the three-dimensional induction logging data obtained in advance to generate a three-dimensional induction logging curve in a wellbore coordinate system;

[0015] Constructing a window function according to the shape feature of the three-dimensional induction logging curve;

[0016] Segmenting the three-dimensional induction logging curve by using the window function;

[0017] Conducting full-parameter inversion on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the hole angle of each horizon; wherein the objective function of the full-parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve.

[0018] In some embodiments of the present application, the shape feature is the shape feature of the three-dimensional induction logging curve at the formation boundary.

[0019] In some embodiments of the present application, before the full-parameter inversion on each segment of the three-dimensional induction logging curve, the method further comprises:

[0020] determining an initial value of the formation boundary according to the XZ component and the ZX component of the three-dimensional induction logging curve.

[0021] In some embodiments of the present application, determining an initial value of the formation boundary according to the XZ component and the ZX component of the three-dimensional induction logging curve comprises:

[0022] determining a cross-component response difference between the XZ component and the ZX component;

[0023] determining the initial value of the formation boundary according to a local maximum value and a local minimum value of the cross-component response difference.

[0024] In some embodiments of the present application, a three-dimensional induction logging data inversion method for deviated well anisotropic formation further comprises:

[0025] determining an order of full parameter inversion on multiple three-dimensional induction logging curves.

[0026] In some embodiments of the present application, the determining an order of full parameter inversion on multiple three-dimensional induction logging curves comprises:

[0027] determining an order of full parameter inversion on a current three-dimensional induction logging curve according to a position segmentation of a total window and a position segmentation of a main window of a window function corresponding to the current three-dimensional induction logging curve.

[0028] In some embodiments of the present application, a three-dimensional induction logging data inversion method for deviated well anisotropic formation further comprises:

[0029] generating a constraint condition of the full parameter inversion according to a relative error of the three-dimensional induction logging data and a formation parameter relative error, and the vertical resistivity is not less than the horizontal resistivity in the full parameter inversion process.

[0030] In a second aspect, the present application provides a three-dimensional induction logging data inversion device for deviated well anisotropic formation, which comprises:

[0031] a logging data conversion module configured to perform azimuth angle conversion on pre-acquired three-dimensional induction logging data to generate three-dimensional induction logging curves in a wellbore coordinate system;

[0032] a window function construction module configured to construct a window function according to a shape feature of the three-dimensional induction logging curve;

[0033] a logging curve segmentation module configured to segment the three-dimensional induction logging curve by using the window function;

[0034] The well logging curve inversion module is configured to perform full parameter inversion on each three-dimensional induction logging curve to obtain horizontal resistivity, vertical resistivity, a formation boundary, and a deviation angle of each horizon. The objective function of the full parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve.

[0035] In some embodiments of the present application, the shape feature is a shape feature of the three-dimensional induction logging curve at the formation boundary.

[0036] In some embodiments of the present application, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0037] The formation boundary initial value determination module is configured to determine an initial value of the formation boundary according to the XZ component and the ZX component of the three-dimensional induction logging curve.

[0038] In some embodiments of the present application, the formation boundary initial value determination module comprises:

[0039] The cross-component response difference determination unit is configured to determine a cross-component response difference between the XZ component and the ZX component.

[0040] The formation boundary initial value determination unit is configured to determine the initial value of the formation boundary according to the local maximum value and the local minimum value of the cross-component response difference.

[0041] In some embodiments of the present application, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0042] The inversion sequence determination module is configured to determine an inversion sequence of full parameter inversion on multiple three-dimensional induction logging curves.

[0043] In some embodiments of the present application, the inversion sequence determination module comprises:

[0044] The inversion sequence determination unit is configured to determine the inversion sequence of the full parameter inversion on the current three-dimensional induction logging curve according to the position segmentation of the total window and the position segmentation of the main window of the window function corresponding to the current three-dimensional induction logging curve.

[0045] In some embodiments of the present application, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0046] The constraint condition generation module is configured to generate a constraint condition of the full parameter inversion according to the relative error of the three-dimensional induction logging data and the relative error of the formation parameter, and the vertical resistivity is not less than the horizontal resistivity in the full parameter inversion process.

[0047] In a third aspect, the present application provides a computer program product comprising computer programs / instructions which, when executed by a processor, implement the steps of the method for inverting three-dimensional induction logging data of anisotropic formation in a deviated well.

[0048] In a fourth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for inverting three-dimensional induction logging data of anisotropic formation in a deviated well when executing the program.

[0049] In a fifth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for inverting three-dimensional induction logging data of anisotropic formation in a deviated well.

[0050] As can be seen from the above description, the embodiments of the present application provide a method and device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well. The corresponding method for inverting three-dimensional induction logging data of anisotropic formation in a deviated well comprises the following steps. First, the three-dimensional induction logging data obtained in advance is subjected to azimuth conversion to generate a three-dimensional induction logging curve in a wellbore coordinate system. Then, a window function is constructed according to the shape features of the three-dimensional induction logging curve. The three-dimensional induction logging curve is segmented by the window function. Finally, full-parameter inversion is performed on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary, and the well deviation angle of each layer. The objective function of the full-parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve.

[0051] The corresponding device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well comprises the following modules. A logging data conversion module is configured to perform azimuth conversion on the three-dimensional induction logging data obtained in advance to generate a three-dimensional induction logging curve in a wellbore coordinate system. A window function construction module is configured to construct a window function according to the shape features of the three-dimensional induction logging curve. A logging curve segmentation module is configured to segment the three-dimensional induction logging curve by the window function. A logging curve inversion module is configured to perform full-parameter inversion on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary, and the well deviation angle of each layer. The objective function of the full-parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve.

[0052] In summary, the application considers the large amount of measured logging data of three-dimensional induction logging data, and performs window segmentation inversion on the logging data to be processed, reduces the influence of surrounding rock, and improves the speed and accuracy of three-dimensional induction logging data processing. The application can quickly invert the three-dimensional induction logging data of the anisotropic formation of the deviated well, greatly shortens the logging data processing time, and improves the working efficiency of the logging instrument. The three-dimensional induction logging data can be better applied to field processing and interpretation and evaluation, and has great significance for the wide application of the three-dimensional induction logging instrument in the field. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0054] Fig. 1 is a flowchart of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0055] Fig. 2 is a coil system structure diagram of the three-dimensional induction logging instrument in the embodiment of the application;

[0056] Fig. 3 is a schematic diagram of the relationship among the formation coordinate system, the borehole coordinate system and the instrument coordinate system in the embodiment of the application;

[0057] Fig. 4 is a schematic diagram of the relationship among the formation coordinate system, the borehole coordinate system and the instrument coordinate system in the embodiment of the application;

[0058] Fig. 5 is a flowchart of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0059] Fig. 6 is a flowchart of step 500 of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0060] Fig. 7 is a flowchart of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0061] Fig. 8 is a flowchart of step 600 of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0062] Fig. 9 is a flowchart of the three-dimensional induction logging data inversion method for anisotropic formation of deviated well in the embodiment of the application;

[0063] Fig. 10 is a flowchart of a method for inverting three-dimensional induction logging data of anisotropic formation in an inclined well according to an embodiment of the present application;

[0064] Fig. 11 is a schematic diagram of constructing a segmented inversion window function according to an embodiment of the present application;

[0065] Fig. 12 is a schematic diagram of dividing logging data according to an embodiment of the present application;

[0066] Fig. 13 is a curve diagram of an iteration inversion error according to an embodiment of the present application;

[0067] Fig. 14 is a schematic diagram of a result of processing logging data after inversion according to an embodiment of the present application;

[0068] Fig. 15 is a block diagram of a device for inverting three-dimensional induction logging data of anisotropic formation in an inclined well according to an embodiment of the present application;

[0069] Fig. 16 is a block diagram of a device for inverting three-dimensional induction logging data of anisotropic formation in an inclined well according to an embodiment of the present application;

[0070] Fig. 17 is a block diagram of a module for determining initial values of formation boundaries according to an embodiment of the present application;

[0071] Fig. 18 is a block diagram of a device for inverting three-dimensional induction logging data of anisotropic formation in an inclined well according to an embodiment of the present application;

[0072] Fig. 19 is a block diagram of a module for determining inversion sequence according to an embodiment of the present application;

[0073] Fig. 20 is a block diagram of a device for inverting three-dimensional induction logging data of anisotropic formation in an inclined well according to an embodiment of the present application;

[0074] Fig. 21 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0075] In order to make the objectives, technical solutions and advantages of embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0076] Those skilled in the art will appreciate that embodiments of the application can be provided as methods, systems, or computer program products. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be in the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) embodying computer readable program code.

[0077] It should be noted that the terms "comprising" and "including" and any variations thereof in the specification and in the claims and the above description of the drawings are intended to cover both the exclusive and the inclusive sense, i.e., the process, method, system, product, or device comprising a series of steps or units includes not only those steps or units clearly listed but also other steps or units that are not clearly listed or inherent to such process, method, product, or device. The embodiments in the application and the features in the embodiments can be combined with each other without conflict. The application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0078] The acquisition, storage, use, processing, etc. of data in the technical solutions of the application comply with relevant provisions of laws and regulations.

[0079] The embodiment of the application provides a specific implementation of a three-dimensional induction logging data inversion method for anisotropic formations in a deviated well, which specifically comprises the following contents with reference to FIG. 1:

[0080] Step 100: azimuth conversion is performed on the pre-acquired three-dimensional induction logging data to generate three-dimensional induction logging curves in a wellbore coordinate system;

[0081] Step 200: a window function is constructed according to the shape features of the three-dimensional induction logging curves;

[0082] Step 300: the three-dimensional induction logging curves are segmented by the window function; and

[0083] Step 400: full-parameter inversion is performed on each segment of the three-dimensional induction logging curves to acquire the horizontal resistivity, the vertical resistivity, the formation boundary, and the well deviation angle of each horizon; wherein the objective function of the full-parameter inversion is that the ZZ component fitting error of the three-dimensional induction logging curves is minimized.

[0084] From the above description, the embodiment of the application provides a three-dimensional induction logging data inversion method for anisotropic formation of a deviated well, which comprises the following steps: first, azimuth conversion is performed on the pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve in a wellbore coordinate system; then, a window function is constructed according to the shape features of the three-dimensional induction logging curve; the three-dimensional induction logging curve is segmented by the window function; finally, full parameter inversion is performed on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the well deviation angle of each horizon; and the objective function of the full parameter inversion is that the ZZ component fitting error of the three-dimensional induction logging curve is minimum.

[0085] In conclusion, the application considers the large amount of measured logging data of the three-dimensional induction logging data, performs window segmentation inversion on the logging data to be processed, reduces the influence of surrounding rock, and improves the speed and accuracy of the three-dimensional induction logging data processing. The application can quickly invert the three-dimensional induction logging data of the anisotropic formation of the deviated well, greatly shortens the logging data processing time, and improves the working efficiency of the logging instrument. The three-dimensional induction logging data can be better applied to field processing and interpretation and evaluation, and has great significance for the wide promotion of the field application of the three-dimensional induction logging instrument.

[0086] For step 100, it can be understood that the three-dimensional induction logging data is acquired by a three-dimensional induction logging instrument in a wellbore, as shown in FIG. 2, the coil system structure of the three-dimensional induction logging instrument is composed of three transmitting coils T x 、T y 、T z , three receiving coils R x 、R y 、R z (parallel to the transmitting coils, with a source distance of L1) and three shielding coils B x 、B y 、B z (parallel to the receiving coils, with a source distance of L2).

[0087] In order to offset the direct coupling component generated by the transmitting coil in the receiving coil, the shielding coil is introduced. The so-called direct coupling refers to the induced signal in the receiving coil due to the closing characteristics of the magnetic flux without passing through the formation when the transmitting signal is transmitted. The winding direction of the shielding coil is opposite to that of the receiving coil, and the number of turns is different. The direct coupling electromotive force generated in the shielding coil and the receiving coil in the air is offset.

[0088] When the transmitting coil system transmits sinusoidal alternating current to the surrounding, nine magnetic field components H ij (i=x, y, z; j=x, y, z) on the receiving coil system can be measured at the same time, wherein H xyHx,Hy,Hz represent the magnetic field strength generated by x-direction emission and y-direction reception, other components are defined similarly.

[0089] In order to investigate the 3D induction logging response in deviated well, three coordinate systems are needed, i.e., the formation coordinate system O-X f Y f Z f , the borehole coordinate system O-X w Y w Z w and the instrument coordinate system O-X t Y t Z t (As shown in Fig. 3 and Fig. 4), the magnetic field tensors in the three coordinate systems satisfy the following rotation transformation rules:

[0090] where,

[0091] In formula (1) and formula (2), α is the borehole inclination angle, defined as the included angle between the Z axis (Z f ) in the formation coordinate system and the Z axis (Z w ) in the borehole coordinate system; and is the instrument azimuth angle, defined as the included angle between the projection of the instrument in the XY plane and the X axis. After compensation, the magnetic field strength measured by the receiving coil system can be represented by the following formula (3):

[0092] In the formula, H ij1 represents the magnetic field generated by the receiving coil, and H ij2 represents the magnetic field generated by the shielding coil. In order to facilitate the comparison between the logging response and the formation electrical parameters, the induction logging response is usually normalized to the measured quantity of conductivity dimension as follows:

[0093] where, is the imaginary part of the coil system magnetic field, K ij is the coil system instrument coefficient,

[0094] In addition, the forward simulation first calculates the electromagnetic field excited by the three orthogonal transmitting coils in the formation coordinate system, obtains the 3D induction logging response in the borehole coordinate system through the coordinate rotation transformation related to the borehole inclination angle α, and then obtains the 3D induction logging response in the instrument coordinate system through the coordinate rotation transformation related to the instrument azimuth angle φ. The actual logging data is always obtained in the instrument coordinate system, so in data processing, the measured data is selected to obtain the logging response curve in the borehole coordinate system through the inverse transformation of the instrument azimuth angle, and then processed.

[0095] For step 200, the morphological characteristics here refer to the morphological characteristics of the three-dimensional induction logging curves at the formation boundaries. That is, the window function is used to reduce the influence of the surrounding rock on the instrument response, and the function shape is constructed based on the instrument response curve shape in the layered formations.

[0096] For step 300, the logging data to be processed is divided into several segments using a window function, and each segment of logging data to be inverted is weighted to reduce the influence of the surrounding rock.

[0097] For step 400, the Gauss-Newton iterative algorithm can be selected for the full parameter inversion. The Gauss-Newton iterative algorithm is a numerical optimization algorithm for nonlinear least squares problems. This nonlinear least squares problem can be formulated as finding a parameter vector that minimizes the sum of squared residuals. The steps of the Gauss-Newton iterative algorithm are as follows:

[0098] Step 1: Initialize the parameter vector, which is generally the initial estimate of the model parameters.

[0099] Step 2: Calculate the residual vector, which is the difference between the actual observed values ​​and the model predictions.

[0100] Step 3: Construct the Jacobian matrix, which contains the partial derivatives of each observation with respect to each parameter.

[0101] Step 4: Calculate the update direction by solving a system of linear equations.

[0102] Step 5: Update the parameter vector.

[0103] Repeat steps 2 to 5 above until the convergence condition is met (e.g., the parameter change is less than a certain threshold).

[0104] In some embodiments of this application, the morphological features are the morphological features of the three-dimensional induction logging curves at the formation boundary.

[0105] That is, the morphological features in step 200 refer to the morphological features of the three-dimensional induction logging curves corresponding to the formation boundaries.

[0106] In some embodiments of this application, referring to Figure 5, before step 400, a method for inverting three-dimensional induction logging data of anisotropic formations in a deviated well further includes:

[0107] Step 500: Determine the initial value of the formation boundary based on the XZ and ZX components of the three-dimensional induction logging curve.

[0108] In 3D inductive logging technology, a multi-component sensing tool is deployed, capable of measuring electromagnetic field components along different directions. Specifically, the XZ and ZX components are measured separately.

[0109] XZ component: refers to the electromagnetic field generated by the transmitter in the X direction, and the response in the Z direction (usually the axial direction of the well). This component can provide information about the conductivity of the horizontal layering of the formation (the layer perpendicular to the well axis).

[0110] ZX component: refers to the electromagnetic field generated by the transmitter in the Z direction, and the response in the X direction (horizontal direction, possibly the lateral direction of the wellbore). This component helps to assess the conductivity of the layer parallel to the well axis.

[0111] In some embodiments of the present application, referring to FIG. 6, step 500 comprises:

[0112] Step 501: determining the cross-component response difference between the XZ component and the ZX component; and

[0113] Step 502: determining the initial value of the formation boundary according to the local maximum and the local minimum of the cross-component response difference.

[0114] Specifically, in step 501 and step 502, the formation is divided according to the local maximum and the local minimum of the cross-component response difference (XZ-ZX), and the initial value of the formation boundary is given;

[0115] In some embodiments of the present application, referring to FIG. 7, the method for inverting the three-dimensional induction logging data of the anisotropic formation of the deviated well further comprises:

[0116] Step 600: determining the order of full parameter inversion of the multi-segment three-dimensional induction logging curve.

[0117] It can be understood that for the multi-segment three-dimensional induction logging curve, an order needs to be determined, and the full parameter inversion of the three-dimensional induction logging curve of each segment is sequentially performed according to the order.

[0118] In some embodiments of the present application, referring to FIG. 8, step 600 comprises:

[0119] Step 601: determining the order of full parameter inversion of the current segment three-dimensional induction logging curve according to the position segmentation of the total window and the position segmentation of the main window of the window function corresponding to the current segment three-dimensional induction logging curve.

[0120] Specifically, given the measured data to be inverted is segmented according to the positions of the total window and the main window, and each segmented data is sequentially inverted. It should be noted that the direction of sequentially inverting each segmented data can be determined according to actual conditions, and the present application does not limit this.

[0121] In some embodiments of the present application, referring to FIG. 9, the method for inverting the three-dimensional induction logging data of the anisotropic formation of the deviated well further comprises:

[0122] Step 700: generating a constraint condition of full parameter inversion according to a relative error of three-dimensional induction logging data and a relative error of formation parameters, and the vertical resistivity is not less than the horizontal resistivity in the full parameter inversion process.

[0123] The relative error of logging response and the relative error of formation parameters are introduced in the inversion process to monitor the convergence of the inversion program, and in addition, some constraint conditions of formation resistivity and anisotropy coefficient are added in the longitudinal one-dimensional inversion objective function; and considering the physical mechanism of the equivalent macroscopic anisotropic formation of thin sand-shale interbedded layers, the formation vertical resistivity is greater than or equal to the formation horizontal resistivity in the iterative inversion process.

[0124] From the above description, it can be known that the embodiment of the application provides a three-dimensional induction logging data inversion method for anisotropic formation of deviated wells, which comprises the following steps.

[0125] In summary, the application considers the large amount of measured logging data of three-dimensional induction logging data, and performs windowed segmented inversion on the logging data to be processed, reduces the influence of surrounding rock, and improves the speed and accuracy of three-dimensional induction logging data processing. The application can quickly invert the three-dimensional induction logging data of anisotropic formation of deviated wells, greatly shortens the logging data processing time, and improves the working efficiency of the logging instrument. The three-dimensional induction logging data can be better applied to field processing and interpretation and evaluation, and has great significance for the wide promotion of the field application of the three-dimensional induction instrument.

[0126] In a specific embodiment, the application further provides a specific embodiment of a three-dimensional induction logging data inversion method for anisotropic formation of deviated wells, as shown in FIG. 10, which specifically comprises the following steps.

[0127] S1: obtaining a three-dimensional induction instrument measurement signal, wherein the measurement signal at least includes a resistivity curve group and a deviation angle.

[0128] Specifically, the three-dimensional induction logging instrument is used for logging to obtain a three-dimensional induction instrument measurement signal (coil system conductivity curve) and a deviation angle.

[0129] S2: constructing a window function.

[0130] The window function is designed to cut the logging data to be processed into several segments, and each segment of logging data to be inverted is weighted to reduce the influence of surrounding rock. The main function of the window function is to reduce the influence of surrounding rock on the instrument response, and the shape of the function is based on the shape of the instrument response curve in the layered formation. The length of the main window is set, for example, the length is 1 / 3 of the length of the total window. Specifically:

[0131] Considering the large amount of measured logging data, the logging data to be processed is cut into several segments, and each segment of logging data is separately windowed and inverted. The existence of surrounding rock will affect the inversion result of the target layer formation parameter. Therefore, the following window function is designed:

[0132] Each segment of logging data to be inverted is weighted to reduce the influence of surrounding rock, and the window function expression is shown in equation (6), wherein w c = 1, w f = 0.1, L is the length of the main window, and z l and z u are the positions of the upper and lower endpoints of the main window, as shown in FIG. 11. Then the logging data is divided into three zones according to the form of the window function, as shown in FIG. 12, the 1st zone and the 3rd zone are surrounding rock zones, and the 2nd zone is the main inversion zone. When the inversion of the 1st zone logging data is completed, the window function will automatically move down by a distance of one main window to reach the 2nd zone. At this time, the 2nd zone in FIG. 12 becomes the surrounding rock zone of this segment of data, and the 3rd zone is the main inversion zone. After iterative inversion, the inversion result of the 3rd zone is output. By moving the window down in turn, the inversion result of the formation parameter of the whole segment can be obtained.

[0133] S3: The measurement data to be inverted is segmented according to the positions of the total window and the main window, and the segmented data is inverted in turn.

[0134] The measurement data to be inverted is segmented according to the positions of the total window and the main window, and each segment of the segmented data is inverted in turn;

[0135] Specifically, before inversion, the initial formation model to be processed (step S5) and the measurement data to be inverted are segmented according to the positions of the total window and the main window, and then each segment of the segmented data is inverted. The inversion uses a longitudinal one-dimensional inversion based on a horizontal layered formation model to obtain a more accurate original formation resistivity, well deviation angle and formation longitudinal boundary position; and an improved Gauss-Newton iterative algorithm is used in the inversion process. The algorithm is as follows:

[0136] Let the logging response data q i (X) = q i (X1, X2,..., X N ), i = 1, 2,..., M (M is the number of acquisition points); X is the parameter to be inverted, and qi (X) is a nonlinear function of X, X = X(σ h ,σ v ,d,α) is the parameter to be inverted. N is the number of variables; for example, for a 5-layer model, N is the sum of 5 horizontal conductivities σ h , 5 vertical conductivities σ v , 4 layer boundaries d and 1 borehole inclination α, which is 15 in total. Now define the objective function:

[0137] where q i (X t ) is the logging response value, and in the absence of measurement noise, X t corresponding to q t is the value of the parameter to be inverted. For the sake of convenience in writing, introduce the vector matrix

[0138] The problem of finding the minimum of the objective function F(X) is usually called the nonlinear least squares problem. Let X (k) be the result of the kth iteration, and according to the Gauss-Newton optimization algorithm, the modification of X, ΔX (k) , can be derived as:

[0139] ΔX (k) = -[J T (X (k) )J(X (k) )] -1 J T (X (k) )f(X (k) ) (10)

[0140] Here J(X) is the Jacobi matrix of F(X):

[0141] The next iteration point X (k+1) is:

[0142] X (k+1) = X (k) + ΔX (k) (12)

[0143] Since ΔX (k) is derived by retaining only the first-order term in the Taylor expansion of f i (X), it is only valid when X (k)Iterative convergence can only be guaranteed when the solution is sufficiently close to the minimum point of the objective function. However, this is sometimes difficult to guarantee, resulting in poor stability of the Gauss-Newton method solution. The solution is prone to getting trapped in local extrema and may even cause the inversion iteration to fail. To overcome this shortcoming, an N×N dimensional diagonal damping matrix B(β) of the following form is introduced, with the matrix elements of B as follows:

[0144] The damping matrix B(β) will gradually approach the identity matrix as the number of iterations increases. That is, the damping effect introduced in this way will automatically decrease and eventually be canceled as the inversion iteration proceeds normally. Then the next iteration point.

[0145] X (k+1) =X (k) +B(β (k) )ΔX (k) (14)

[0146] The parameter β can take values ​​ranging from 0.5 to 1.

[0147] Introducing relative error of logging response during inversion process Relative error with formation parameters To monitor the convergence of the inversion procedure, the two parameters are defined as follows:

[0148] In the formula, n is the total number of logging curves, m is the number of measurement points for each logging curve, N is the total number of vertical layers in the formation model, and d i Let R be the boundary location of the i-th layer, α be the wellbore dip angle, and R be the depth of the well. hi Let R be the horizontal resistivity of the i-th formation. vi Let be the vertical resistivity of the i-th stratum.

[0149] S4: Delineate strata based on the cross-component response difference (XZ-ZX).

[0150] Strata are delineated based on the local maxima and minima of the cross component response difference (XZ-ZX), with initial values ​​for the stratigraphic boundaries given.

[0151] S5: Given the initial stratigraphic model for inversion processing.

[0152] In addition, the following initial values ​​need to be provided: well inclination angle, formation horizontal resistivity, and formation vertical resistivity.

[0153] S6: Perform full-parameter inversion to obtain the formation horizontal resistivity, vertical resistivity, and well inclination angle.

[0154] The Gauss-Newton iterative algorithm is used for full parameter inversion.

[0155] S7: When the fitting error of the ZZ component is minimized, the iterative inversion ends.

[0156] Specifically, when the fitting error of the ZZ component reaches its minimum, the iterative inversion ends, and the formation horizontal resistivity, vertical resistivity, formation boundary and well inclination angle are obtained.

[0157] In the vertical one-dimensional inversion objective function, certain constraints need to be added to limit the formation resistivity and anisotropy coefficient:

[0158] (1) Considering the physical mechanism of equivalent macroscopic anisotropic strata in thin alternating sandstone and mudstone layers, the vertical resistivity of the strata must be greater than or equal to the horizontal resistivity R during the iterative inversion process. v ≥R h .

[0159] (2) Anisotropy coefficient λ of anisotropic strata 2 =R v / R h The limit is generally set below 20, mainly because three-dimensional induction logging instruments have relatively low sensitivity to vertical resistivity, making it difficult to accurately invert vertical resistivity with anisotropy coefficients greater than 20.

[0160] The following uses a deviated well anisotropic TI formation model as an example to illustrate and verify the method of rapid inversion of three-dimensional induction logging data using windowing functions. Table 1 shows a typical thin interbedded anisotropic (TI) formation model. The three-dimensional induction instrument transmission frequency is f = 25 kHz. A long source-spacing coil system with less wellbore influence is preferred: main receiving coil source-spacing L1 = 63 in, shielding coil source-spacing L2 = 49.5 in, where 1 in = 2.54 cm, and wellbore inclination α = 60°. Given initial inversion values: wellbore inclination α0 = 55°, horizontal conductivity R h0 =1.5R h Vertical conductivity R v0 =1.5R v Considering the actual measurement situation, the simulated response plus 3% random noise is used as the measured signal for inversion.

[0161] Table 1 Anisotropic TI Stratigraphic Model

[0162] The variation of inversion iteration error with iteration number n is shown in Fig. 13. In the figure, S is defined as the relative error of logging response fitting (%) according to formula (15); Sp is defined as the relative error of formation parameter fitting (%) according to formula (16); S Rh is defined as the relative error of horizontal resistivity fitting (%) according to formula (16); SRV is defined as the relative error of vertical resistivity fitting (%) according to formula (16); Sh is defined as the relative error of longitudinal boundary fitting (%) according to formula (16); and S alpha is defined as the relative error of hole inclination fitting (%) according to formula (16). It can be seen from Fig. 13 that the stability and convergence speed of inversion iteration are very good. Even in the case of considering the noise effect, the relative error of logging response and the relative error of formation parameter are quickly converged within 10 steps. The resistivity processing result obtained after iteration inversion is shown in Fig. 14, and the specific data of the inversion result is shown in Table 2. It can be seen from Table 2 and Fig. 14 that the accuracy of hole inclination obtained by the fast inversion is very high, the horizontal resistivity R h and the vertical resistivity R v obtained by the fast inversion are also very good, which shows that the fast inversion method is feasible and satisfactory results are obtained.

[0163] Table 2 Real parameters of formation model and inversion results

[0164] From the above description, it can be known that the embodiment of the application provides a three-dimensional induction logging data inversion method for anisotropic formation in a deviated well, which comprises the following steps: first, performing azimuth angle conversion on the pre-acquired three-dimensional induction logging data to generate three-dimensional induction logging curves in a wellbore coordinate system; then, constructing a window function according to the shape features of the three-dimensional induction logging curves; segmenting the three-dimensional induction logging curves through the window function; and finally, performing full-parameter inversion on each segment of the three-dimensional induction logging curves to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the hole inclination of each horizon; wherein the objective function of the full-parameter inversion is that the ZZ component fitting error of the three-dimensional induction logging curves is the minimum.

[0165] The above method considers that the amount of measured logging data is large, and the logging data to be processed is subjected to window segmentation one-dimensional inversion, which reduces the influence of surrounding rock and improves the speed and accuracy of three-dimensional induction instrument logging data processing. The damping matrix and the constraint condition are introduced in the inversion process to improve the stability of the inversion program.

[0166] In summary, this application enables rapid inversion of 3D induction logging data from anisotropic formations in deviated wells, significantly shortening data processing time, improving the efficiency of logging instruments, and substantially reducing the cost of on-site testing. This allows 3D induction logging data to be better applied to field processing and interpretation, which is of great significance for the widespread application of 3D induction instruments in the field. For example, based on the horizontal resistivity, vertical resistivity, formation boundaries, and well inclination angle of each layer, oil and gas field development plans can be optimized, thereby controlling equipment used for oil and gas field development to perform extraction operations more efficiently.

[0167] Based on the same concept, this application also provides a device for inverting three-dimensional induction logging data of anisotropic formations in deviated wells, which can be used to implement the method described in the above embodiments, as shown in the following embodiments. Since the principle of solving the problem using the device for inverting three-dimensional induction logging data of anisotropic formations in deviated wells is similar to that of the method for inverting three-dimensional induction logging data of anisotropic formations in deviated wells, the implementation of the device can refer to the implementation of the method for inverting three-dimensional induction logging data of anisotropic formations in deviated wells, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0168] This application provides a specific implementation of a three-dimensional induction logging data inversion device for deviated well anisotropic formations capable of realizing a three-dimensional induction logging data inversion method for deviated wells. Referring to Figure 15, the device includes:

[0169] The logging data conversion module 10 is used to convert the azimuth angle of the pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve in the wellbore coordinate system.

[0170] Window function construction module 20 is used to construct window functions based on the morphological characteristics of three-dimensional induction logging curves;

[0171] The logging curve segmentation module 30 is used to segment the three-dimensional induction logging curve using window functions; and

[0172] The logging curve inversion module 40 is used to perform full-parameter inversion on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, vertical resistivity, formation boundary and well inclination angle of each layer; among them, the objective function of the full-parameter inversion is to minimize the fitting error of the ZZ component of the three-dimensional induction logging curve.

[0173] In some embodiments of this application, the morphological features are the morphological features of the three-dimensional induction logging curves at the formation boundary.

[0174] In some embodiments of the present application, referring to FIG. 16, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0175] The initial value determination module 50 is configured to determine the initial value of the formation boundary according to the XZ component and the ZX component of the three-dimensional induction logging curve.

[0176] In some embodiments of the present application, referring to FIG. 17, the initial value determination module 50 comprises:

[0177] The cross-component response difference determination unit 50a is configured to determine the cross-component response difference between the XZ component and the ZX component; and

[0178] The initial value determination unit 50b is configured to determine the initial value of the formation boundary according to the local maximum value and the local minimum value of the cross-component response difference.

[0179] In some embodiments of the present application, referring to FIG. 18, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0180] The inversion sequence determination module 60 is configured to determine the sequence of full parameter inversion of the multi-segment three-dimensional induction logging curve.

[0181] In some embodiments of the present application, referring to FIG. 19, the inversion sequence determination module 60 comprises:

[0182] The inversion sequence determination unit 60a is configured to determine the sequence of full parameter inversion of the current segment three-dimensional induction logging curve according to the position segmentation of the total window and the position segmentation of the main window of the window function corresponding to the current segment three-dimensional induction logging curve.

[0183] In some embodiments of the present application, referring to FIG. 20, the device for inverting three-dimensional induction logging data of anisotropic formation in a deviated well further comprises:

[0184] The constraint condition generation module 70 is configured to generate the constraint condition of the full parameter inversion according to the relative error of the three-dimensional induction logging data and the relative error of the formation parameter, and the vertical resistivity is not less than the horizontal resistivity in the full parameter inversion process.

[0185] From the above description, the embodiment of the application provides a device for inverting three-dimensional induction logging data of anisotropic formation of an inclined shaft, comprising: a logging data conversion module, configured to perform azimuth angle conversion on the pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve in a wellbore coordinate system; a window function construction module, configured to construct a window function according to the shape feature of the three-dimensional induction logging curve; a logging curve segmentation module, configured to segment the three-dimensional induction logging curve through the window function; and a logging curve inversion module, configured to perform full parameter inversion on each segment of the three-dimensional induction logging curve to acquire the horizontal resistivity, the vertical resistivity, the formation boundary and the inclination angle of each horizon; wherein the objective function of the full parameter inversion is to minimize the ZZ component fitting error of the three-dimensional induction logging curve.

[0186] In summary, the application considers the large amount of measured logging data of three-dimensional induction logging data, and performs windowed segmentation inversion on the logging data to be processed, reduces the influence of surrounding rock, and improves the speed and accuracy of three-dimensional induction instrument logging data processing. The application can quickly invert the three-dimensional induction logging data of anisotropic formation of an inclined shaft, greatly shortens the logging data processing time, and improves the working efficiency of the logging instrument. The three-dimensional induction instrument logging data can be better applied to field processing and interpretation and evaluation, and has great significance for the wide application of the three-dimensional induction instrument in the field.

[0187] The embodiment of the application also provides a specific implementation of an electronic device capable of implementing all steps of the three-dimensional induction logging data inversion method of anisotropic formation of an inclined shaft in the above embodiment, as shown in FIG. 21, which specifically includes the following contents:

[0188] A processor 1201, a memory 1202, a communications interface 1203 and a bus 1204;

[0189] The processor 1201, the memory 1202 and the communications interface 1203 communicate with each other through the bus 1204; the communications interface 1203 is configured to realize information transmission between the server-side device, the client-side device and other related devices;

[0190] The processor 1201 is configured to call the computer program in the memory 1202, and the processor performs the computer program to realize all steps of the three-dimensional induction logging data inversion method of anisotropic formation of an inclined shaft in the above embodiment, for example, the processor performs the computer program to realize the following steps:

[0191] Step 100: performing azimuth angle conversion on the pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve in a wellbore coordinate system;

[0192] Step 200: constructing a window function according to the shape features of the three-dimensional induction logging curve;

[0193] Step 300: segmenting the three-dimensional induction logging curve through the window function; and

[0194] Step 400: performing full parameter inversion on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the well inclination angle of each horizon; wherein the objective function of the full parameter inversion is that the ZZ component fitting error of the three-dimensional induction logging curve is minimum.

[0195] The embodiments of the present application also provide a computer readable storage medium capable of implementing all steps in the inclined well anisotropic formation three-dimensional induction logging data inversion method in the above embodiments, and the computer readable storage medium stores a computer program. When the computer program is executed by a processor, all steps of the inclined well anisotropic formation three-dimensional induction logging data inversion method in the above embodiments are implemented, for example, the processor executes the computer program to implement the following steps:

[0196] Step 100: performing azimuth angle conversion on the pre-acquired three-dimensional induction logging data to generate a three-dimensional induction logging curve in a wellbore coordinate system;

[0197] Step 200: constructing a window function according to the shape features of the three-dimensional induction logging curve;

[0198] Step 300: segmenting the three-dimensional induction logging curve through the window function; and

[0199] Step 400: performing full parameter inversion on each segment of the three-dimensional induction logging curve to obtain the horizontal resistivity, the vertical resistivity, the formation boundary and the well inclination angle of each horizon; wherein the objective function of the full parameter inversion is that the ZZ component fitting error of the three-dimensional induction logging curve is minimum.

[0200] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other. Each embodiment mainly describes the difference from other embodiments. Especially, for the hardware+program type embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the related parts can be referred to the part of the method embodiment.

[0201] The above-described embodiments of the application have several aspects, no single one of which is solely responsible for the application's desirable attributes. Without limiting the scope of this application as to its specific aspects, some advantages thereby made possible are listed below.

[0202] Although this application provides method operations steps as in embodiments or flowcharts, more or less operations steps can be included based on conventional or non-creative labor. The order in which the steps are listed in embodiments is only one of the many ways to execute the steps, and does not represent the only way to execute the steps. In actual device or client product execution, the method order shown in embodiments or drawings can be executed in sequence or in parallel (such as in parallel processor or multi-threaded processing environment).

[0203] For the convenience of description, the above device is described as various modules respectively described in function. Of course, in the implementation of the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules implementing the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0204] Those skilled in the art also know that, in addition to implementing the controller in the form of pure computer readable program code, the controller can also be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded microcontrollers, etc. by logically programming the method steps to achieve the same function. Therefore, such a controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the devices for implementing various functions can also be considered as both software modules implementing the method and structures within the hardware component.

[0205] In one typical arrangement, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0206] Memory can include non-persistent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory such as read only memory (ROM) or flash memory, etc. Memory is an example of computer-readable media.

[0207] Each of the embodiments in the present specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the description of the method embodiments. In the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present specification. The illustrative representation of the above terms in the present specification does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, a person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0208] The above only describes the embodiments of the embodiments of the present specification and does not limit the embodiments of the present specification. Those skilled in the art can make various changes and modifications to the embodiments of the present specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification shall be included in the scope of the claims of the embodiments of the present specification.

Claims

1. A method for inverting three-dimensional induction logging data in a deviated well in an anisotropic formation, characterized in that, The method comprises: conducting azimuthal conversion on pre-acquired three-dimensional induction logging data to generate three-dimensional induction logging curves in a wellbore coordinate system; constructing a window function according to a shape feature of the three-dimensional induction logging curves; segmenting the three-dimensional induction logging curves through the window function; and conducting full-parameter inversion on each segment of the three-dimensional induction logging curves to obtain horizontal resistivity, vertical resistivity, a formation boundary, and a deviation angle of each horizon; wherein an objective function of the full-parameter inversion is to minimize a ZZ-component fitting error of the three-dimensional induction logging curves.

2. The method of inverting inclined well anisotropic formation 3D induction logging data according to claim 1, characterized in that, The shape feature is a shape feature of the three-dimensional induction logging curves at the formation boundary.

3. The method of claim 1, wherein, Before the full-parameter inversion on each segment of the three-dimensional induction logging curves, the method further comprises: determining an initial value of the formation boundary according to an XZ component and a ZX component of the three-dimensional induction logging curves.

4. The method of claim 3, wherein, Determining the initial value of the formation boundary according to the XZ component and the ZX component of the three-dimensional induction logging curves comprises: determining a cross-component response difference between the XZ component and the ZX component; and determining the initial value of the formation boundary according to local maximum values and local minimum values of the cross-component response difference.

5. The method of claim 1, wherein, The method further comprises: determining an order of full-parameter inversion on multiple segments of the three-dimensional induction logging curves.

6. The method of inverting inclined well anisotropic formation 3D induction logging data according to claim 5, characterized in that, The determining of the order of full-parameter inversion on multiple segments of the three-dimensional induction logging curves comprises: determining the order of full-parameter inversion on a current segment of the three-dimensional induction logging curves according to a position segmentation of a total window and a position segmentation of a main window of a window function corresponding to the current segment of the three-dimensional induction logging curves.

7. The method of inverting inclined well anisotropic formation 3D induction logging data according to any one of claims 1 to 6, characterized in that, The method further comprises: generating a constraint condition of the full-parameter inversion according to a relative error of the three-dimensional induction logging data and a formation parameter relative error, and the vertical resistivity is not less than the horizontal resistivity in the full-parameter inversion process.

8. A device for inverting three-dimensional induction logging data of anisotropic formations in inclined wells, characterized in that, The method comprises: a logging data conversion module configured to conduct azimuthal conversion on pre-acquired three-dimensional induction logging data to generate three-dimensional induction logging curves in a wellbore coordinate system; a window function construction module configured to construct a window function according to a shape feature of the three-dimensional induction logging curves; a logging curve segmentation module configured to segment the three-dimensional induction logging curves through the window function; and a logging curve inversion module configured to conduct full-parameter inversion on each segment of the three-dimensional induction logging curves to obtain horizontal resistivity, vertical resistivity, a formation boundary, and a deviation angle of each horizon; wherein an objective function of the full-parameter inversion is to minimize a ZZ-component fitting error of the three-dimensional induction logging curves.

9. The apparatus of claim 8, wherein, The shape feature is a shape feature of the three-dimensional induction logging curves at the formation boundary.

10. The apparatus of claim 8, wherein, The method further comprises: a formation boundary initial value determination module configured to determine an initial value of the formation boundary according to an XZ component and a ZX component of the three-dimensional induction logging curves.

11. The apparatus of claim 10, wherein, The formation boundary initial value determination module comprises: a cross-component response difference determination unit configured to determine a cross-component response difference between the XZ component and the ZX component; and a formation boundary initial value determination unit configured to determine the initial value of the formation boundary according to local maximum values and local minimum values of the cross-component response difference.

12. The apparatus of claim 8, wherein, The method further comprises: An inversion sequence determining module is configured to determine an inversion sequence of full parameter inversion on multi-section three-dimensional induction logging curves.

13. The apparatus of claim 12, wherein, The inversion sequence determining module comprises: An inversion sequence determining unit is configured to determine an inversion sequence of full parameter inversion on a current section three-dimensional induction logging curve according to position segmentation of a total window and position segmentation of a main window of a window function corresponding to the current section three-dimensional induction logging curve.

14. The apparatus of any one of claims 8 to 13, wherein, Further comprising: A constraint condition generating module is configured to generate a constraint condition of the full parameter inversion according to relative errors of the three-dimensional induction logging data and relative errors of formation parameters, and the vertical resistivity is not less than the horizontal resistivity in the full parameter inversion process.

15. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instruction is executed by the processor to implement the steps of the three-dimensional induction logging data inversion method of anisotropic formation in a deviated well according to any one of claims 1 to 7.

16. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps of the three-dimensional induction logging data inversion method of anisotropic formation in a deviated well according to any one of claims 1 to 7.

17. A computer readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to implement the steps of the three-dimensional induction logging data inversion method of anisotropic formation in a deviated well according to any one of claims 1 to 7.

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